Global Localization Using Low-frequency Image-based Descriptor and Range Data-based Validation

Chansoo Park, Jae Bok Song

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In image-based global localization, a robot pose is estimated through image association when the robot revisits a previously visited location on a map. Image association is typically performed using high-level local features such as scale invariant feature transform (SIFT) and speeded up robust feature (SURF). However, these methods suffer from false-positive association and high computational load to reject outliers. In this study, we introduce a novel global localization method based on the proposed low-frequency image-based descriptor (LFID) and laser range data. The image is first processed by reducing the range of luminance in the frequency domain. Visual features are then extracted from the processed image through a kernel window. These visual features are described as binary representation for fast association. Because this binary representation includes a spatial distribution of features, it can minimize false-positive association. Nevertheless, false-positive association could occur when scenes appear to be similar from different viewpoints. To address this problem, this study adopts a laser rangefinder to validate the similarity of the place and reject false-positives from the scene recognition. Experimental results confirm the effectiveness of the proposed scheme in actual indoor environments.

Original languageEnglish
Pages (from-to)1332-1340
Number of pages9
JournalInternational Journal of Control, Automation and Systems
Volume16
Issue number3
DOIs
Publication statusPublished - 2018 Jun 1

Bibliographical note

Funding Information:
Manuscript received August 4, 2016; revised July 18, 2017; accepted November 15, 2017. Recommended by Associate Editor Dong-Joong Kang under the direction of Editor Fuchun Sun. This research was supported by the MOTIE under the Industrial Foundation Technology Development Program supervised by the KEIT (No. 10084589).

Publisher Copyright:
© 2018, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • Global localization
  • low-frequency image-based descriptor
  • range data validation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications

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